Innovation through Machine Learning…

Very innovative… As someone who has recently supported a near one post a stroke, I see that there is hopefully new innovation here using @machinelearning to save lives..

Improving stroke treatment through machine learning

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Reinvigorate Customer Experiences by Harnessing Power of Analytics

Today’s organizations are facing multiple drivers in the race to get ahead of the competition and drive greater revenues. These drivers could be increasing customer expectations and new buying behaviors, disruptive product innovation, increasing demand for regulatory compliance and risk awareness or increased profitability measures. We are now poised to enter a new era of customer experience management in which winning organizations will move beyond measuring customer satisfaction and defection only to approaches based on a broader understanding of customer considering a more holistic set of data that is both internal to the organization and available externally in the social ecosystem.

Customer Experience Management is underpinned by a clear focus on a set of main pillars, namely, loyalty, retention, migration. Research has shown that the total value at stake from customer migration – defined as significant changes in customer relationships up or down – is more than 10 times the value of defection alone. Winning organizations are looking at positive disruptive innovation using techniques like analytics to drive new insights around understanding customer behavior patterns and better positioning of products and services for increased acceptance leading to revenue and thereby profit.

Challenges & Missed Opportunities :Businesses today are mostly missing insights in identifying most important customers and mitigating the risk of these customers moving to a competitor. There is a lacking in understanding of the holistic customer profile, customer migration patterns and behavior that hinders targeted marketing, service and sales campaigns. Knowing which products are best to offer their existing customers depending upon change in buying patterns. Another key challenge is the lack of understanding customer profitability and upsell opportunities that has been tailored to the migration patterns and buying behavior. Added to this is the ability to capture customer web and social preferences including market sentiment data to drive better insights for marketing and sales.

Some key compelling events include the rise in customer attrition / migration for a line of business, region or distribution channel but the organization does not know why. Organization is unable to achieve premium growth targets with just new business. Up-sell and cross-sell initiatives are not achieving target growth objectives as they are not targeted to a specific customer profile / demographic.

This could be due to red flags such as silo-ed line of business approach due to technical infrastructure or by current business process and service model, minimal investments in web and social media initiatives to capture complete data set for customer and the key fact that customer data is fragmented across multiple systems and repositories

Business Goal/Objectives : Thriving businesses can leverage the power of advanced analytics solutions and the ability of factoring both internal and external customer data to drive better understanding of customer migration and satisfaction patterns. This process includes assimilating technology with analytics strategy while identifying quantifiable goals for improving customer satisfaction thereby resulting in better customer retention with a direct impact on improved revenue and profit margins.

Trends in the Industry : Since the recent emphasis on the use of analytics in almost every sector, industry leaders are embarking on leveraging actionable intelligence to monitor internal and external customer data, predict outcomes and to create new revenue sources. It is an established fact that acquiring new customers can cost as much as five times more than satisfying and retaining current customers. A Data monitor report noted that a large Midwest US insurance company could boost their direct premiums by $1M by increasing their customer retention by 1%. Customer retention calculation is not just about keeping good customers but also understanding their behaviors when acquiring new customers and allowing poor performing customers to exit.

In the insurance sector for example, companies can no longer rely on investment income to achieve shareholder profit demands since the economic collapse. Sustaining continuous incoming premium generated by profitable satisfied customers is paramount. The same principle applies to attrition within agent driven businesses where agent satisfaction and retention is key to increasing revenue and improving margins.

Within the Automotive sector, manufacturers are increasing using advanced analytics to understand customer buying behavior, migration and churn patterns and studying product affinities in order to improve cross-sell and up-sell opportunities. In Retail and CPG sector, improved customer satisfaction, quality, retention and loyalty efforts are being driven by adoption of analytical techniques to:

  • Address growth of constantly connected consumers with local needs; the consumer sometimes knows more than retail salespeople
  • Bring innovative offerings such as personal shoppers, to market rapidly; precisely target consumer needs
  • Understand the big picture, including consumers, partners, competition
  • Streamline the buying process using integrated mobile banking
  • Focus on consumer-related data rather than product-related data
  • Gain unique insights into market risks
  • Adjust strategy continually to the evolving market and marketplace

Key Stakeholders: The Chief Marketing Office (CMO), is responsible for sales management, product development and distribution channel management. The CMO creates the strategy to target the right segment of the customer base to ensure retention, cross-sell/up-sell and profitability. The Line of business owner is ultimately accountable for revenue management and profit. The CIO community across many industry sectors are also actively contributing to the adoption of analytical techniques to drive realization of business use cases in improving customer satisfaction and retention.

Solution Point of View : The idea is to reinvigorate customer experience by leveraging advanced analytics focusing on KPIs that are driven towards customer analytics models and supported by an agile platform to meet specific satisfaction (CSAT) and retention goals. The solution should be holistic and drive complete lifecycle support including:

  • Customer Experience Strategy Alignment– baselines the current customer satisfaction and retention efforts, agree on goals, assesses use of data and underlying technology to develop an actionable set of recommendations, roadmap and business case
  • Customer Experience Analytics Realization and Call to Action– Implements analytics to deliver satisfaction and retention KPIs by sourcing and integrating important customer data from social media and third party feeds, building analytic models for CSAT, visualizations and utilizing results to embed new insights into marketing and operations with measurable and verifiable results

Having developed predicitive analytical models that are help organizations to assess their customer’s value, more accurately target marketing campaigns, create tiered service programs to serve customers commensurate with their value to the company and improve customer retention according to the designed strategy, with measured and verifiable results.

Value Impact: The value of in-house customer data can be enhanced further by combining it with relevant external data. Such capability will unveil additional untapped information which will translate into revenue. The value of using analytics to arrive at patterns for understanding customer behavior is significant in terms of the direct correlation to revenue recognition and improving profit margins.

Thank you for reading my post. I regularly write about enterprise transformation and performance management using disruptive innovation in digital solutions including Big Data, Analytics, Cloud, Social, Mobile and Enterprise Architecture. If you would like to read my regular posts then please feel free to also connect on Linkedin, via Twitter, and on my blog on “The Business of IT

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